The Tableau Performance Checklist: Filtering – Avoid High-Cardinality Quick Filters

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The Tableau Performance Checklist: Filtering – Avoid High-Cardinality Quick Filters

by Tim Costello

The Tableau Performance Checklist series is designed to help you streamline your dashboard performance and Tableau Server configuration. Each post expands upon one item listed in the master Tableau Performance Checklist.

The next item in our Filtering checklist is:

“Avoid high-cardinality quick filters (multi-select or drop-down lists). High-cardinality quick filters are slow to load and render.”

Let’s jump right in and see how high cardinality in your quick filters can negatively impact performance.

What is Cardinality?

In SQL, the cardinality of a set is the number of unique values in a particular column. For instance, the cardinality of the states in the United States is fifty because there are fifty unique values regardless of how many rows there are in that column. Cardinality is normally classified into three categories:

  • High-cardinality: These columns have values that have very rare values or are unique. An example of high-cardinality column values might be unique identifiers or email addresses.
  • Normal-cardinality: The normal category has values that are somewhat uncommon. An example might be customer last names. There are some names that are common, such as “Jones,” but there would be values that are very uncommon, such as “Jahanshahi.”
  • Low-cardinality: These refer to column values that have very few unique values. Some examples would include Boolean values or major classifications such as gender.

Naturally, when you have a quick filter appearing in your visualization, the cardinality of the set will determine how many filter options will appear in the filter.

The Problem

The problem with high-cardinality quick filters is, of course, that Tableau must query and return all of the values in the quick filter if you use a drop-down list. If you have a lot of values in the quick filter to choose from, then it incrementally adds to the things that Tableau must do before your visualization can finish loading.

If you use the Best Practice Analyzer tool from our Workbook Tools for Tableau, it will return high-cardinality quick filters as a flag. In addition, it will even return the number of unique values in the high-cardinality column as an extra piece of information.

A Wild Solution

The best way to fix this potential problem is to remove the drop-down option from the quick filter. Instead, consider using a Wildcard option instead. This allows the report user to begin entering characters, and Tableau will provide a list of matches that they can select. This reduces the upfront processing time to get the visualization functioning. When you start looking for a filter value, Tableau will not have to load the full scope of unique values in the quick filter.

Wildcard

Changing the quick filter type is quite easy. Just click on the down arrow on the dashboard and select Wildcard Match. Then, when you enter in a few characters, Tableau will return all values that match those characters.

Wildcard Match

Mastering Best Practices

If you’re interested in becoming a Tableau Server guru, then learning these performance best practices is essential. Check back frequently as we add new posts and dive deeper into each point in the Tableau Performance Checklist.

Another great way to identify best practices is to leverage the insights offered by our Performance Analyzer, part of Workbook Tools for Tableau. It will examine all of your workbooks, worksheets, dashboards and data sources against a list of best practices to ensure that you’re using all the tips and tricks to guarantee your visualizations are moving at light speed.

As always, feel free to get in touch with us if you have any questions regarding performance or anything Tableau related! We’d be happy to help.

Contact Us!

Want More The Tableau Performance Checklist

  1. The Tableau Performance Checklist
  2. The Tableau Performance Checklist: Data – Keep Analysis Simple
  3. The Tableau Performance Checklist: Data – Bring in Only Needed Data
  4. The Tableau Performance Checklist: Data – Use ‘Describe’ to Explore
  5. The Tableau Performance Checklist: Data – Remove Unused Columns from Extracts
  6. The Tableau Performance Checklist: Data – Use One TDS File
  7. The Tableau Performance Checklist: Data – Use Extracts
  8. The Tableau Performance Checklist: Filtering – Minimize Quick Filters
  9. The Tableau Performance Checklist: Filtering – Avoid ‘Only Relevant Values’ in Quick Filters
  10. The Tableau Performance Checklist: Filtering – Avoid High-Cardinality Quick Filters
  11. The Tableau Performance Checklist: Filtering – Avoid Quick Filters That Drive Context Filters
  12. The Tableau Performance Checklist: Filtering – Keep Range Quick Filters Simple
  13. The Tableau Performance Checklist: Filtering – Use Dashboard Filter Actions
  14. The Tableau Performance Checklist: Filtering – Don’t Be Lazy with User Filters
  15. The Tableau Performance Checklist: Custom SQL – Limit in Live Connections
  16. The Tableau Performance Checklist: Custom SQL – Avoid Parameters
  17. The Tableau Performance Checklist: Custom SQL – Watch for Useless Clauses
  18. The Tableau Performance Checklist: Calculations – Use Calculated Fields Carefully
  19. The Tableau Performance Checklist: Calculations – Limit Blended Calculations
  20. The Tableau Performance Checklist: Calculations – Avoid Row-Level Calculations Involving Parameters
  21. The Tableau Performance Checklist: Rendering – Avoid High Mark Counts
  22. The Tableau Performance Checklist: Rendering – Limit Text Tables With Lots of Marks
  23. The Tableau Performance Checklist: Rendering – Minimize Image & Shape File Sizes
  24. The Tableau Performance Checklist: Rendering – Use Transparent Background PNGs
  25. The Tableau Performance Checklist: Local Computations – Server Performance
  26. The Tableau Performance Checklist: Local Computations – Table Calculations
  27. The Tableau Performance Checklist: Dashboard Layout – Limit Number of Worksheets
  28. The Tableau Performance Checklist: Dashboard Layout – Fix Dashboard Size

More About the Author

Tim Costello

Analytics Consultant
3 Reasons Why You Should Want a Data Warehouse I hear a lot of reasons people avoid a data warehouse: It takes too long to build, data warehouse projects are expensive and often end ...
The Tableau Performance Checklist: Filtering – Avoid High-Cardinality Quick Filters The next item in our Filtering checklist is: “Avoid high-cardinality quick filters (multi-select or drop-down lists). ...

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